There is a fundamental gap in understanding how anti-depressants interact with their drug targets at the molecular level. Continued existence of this gap represents an important problem in terms of rationally designing or developing new therapeutics for mental illnesses. The long-term goal of our research is to understand how clinically relevant anti-depressant compounds interact with their biochemical targets at the molecular level. The objective of this application is to develop and utilize photoaffinity probes based on citalopram and fluoxetine, clinically significant compounds for treating depression and other mental illnesses, to map their corresponding binding sites and poses within the serotonin transporter (SERT). The central hypothesis is that these selective serotonin reuptake inhibitors (SSRIs) can be derivatized with a photoreactive group and a bioorthogonal tag for application of click chemistry proteomic techniques. After specific crosslinking, tagged SERT will be proteolyzed and mass fingerprinted, and crosslinked peptides will be analyzed in LC-MS/MS studies to identify the specific sites of covalent attachment of each probe. Our novel approach couples photoaffinity labeling with sensitive mass spectrometry (MS) to directly identify sites of interaction of photoprobes with the SERT. Identification of these sites will allow for refinement o our molecular modeling studies that map ligand-binding poses and sites within SERT. The rationale that underlies the proposed research is that, once it is known how SSRIs interact with the SERT, lead compounds can then be rationally manipulated as potential drug candidates for a host of mental illnesses. The central hypothesis will be tested by pursuing two specific aims: 1) Development of a library of SSRI-based photoprobes for labeling SERT; and 2) Identification of the irreversible attachment sites for the photoprobes within SERT. Under the first aim, citalopram and fluoxetine will be structurally modified to contain a photoreactive group (e.g., ary azide, benzophenone) and clickable tag (e.g., terminal alkyne, aliphatic azide), followed by SERT pharmacological evaluation to identify suitable photoprobes for proteomic characterization. Under the second aim, SERT photoaffinity labeling coupled with MS will identify specific drug-protein contacts for photoprobes developed in Aim 1. All results will be coupled with SERT molecular modeling in order to refine our computational models and accurately map the ligand-binding poses and sites for citalopram and fluoxetine within the transporter. The research is innovative because it uses a tandem photoaffinity labeling-bioorthogonal conjugation chemical proteomics approach to directly map the sites of SSRI interactions in SERT. The proposed research is significant, because it is expected to vertically advance and expand our understanding of how SSRIs, as clinically relevant anti-depressant compounds, interact with their major drug target at the molecular level. Ultimately, such knowledge has the potential to guide future ligand optimization of drug candidates for numerous SERT-implicated disorders (e.g., depression, anxiety, autism, obsessive- compulsive disorder) and refine SERT molecular models for computer-aided drug discovery efforts (i.e., virtual / in silico screening, structure-based drug design).